Evidence map›Paper›PMID 42082581›Full record

ArticleScientific reports2026

An empirical study on teachers' attitudes and digital competencies in Jiangxi, China: gender as a moderating factor.

Qing Gui, Muhd Khaizer Omar, Ahmad Salahuddin Mohd Harithuddin

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Qing GuiUniversiti Putra Malaysia, Kuala Lumpur, Malaysia. guiqing.0827@163.com.
Muhd Khaizer OmarUniversiti Putra Malaysia, Kuala Lumpur, Malaysia.
Ahmad Salahuddin Mohd HarithuddinUniversiti Putra Malaysia, Kuala Lumpur, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Faced with technological advancements in the digital era, this study explores the relationships between teachers' attitudes toward the use of Information and Communication Technology (ICT) in teaching, their digital competencies, and the moderating role of gender. Integrating the Tripartite Model of Attitudes (ABC Model), the Technological Pedagogical Content Knowledge (TPACK) framework, and the Unified Theory of Acceptance and Use of Technology (UTAUT), this research quantitatively assesses attitudes and digital competencies using validated instruments among a sample of 386 TVET teachers from a higher vocational school in Jiangxi Province, China. Findings revealed that teachers generally exhibit moderate levels of digital competencies and hold positive attitudes toward ICT use. Teachers' attitudes were significantly associated with their digital competencies, indicating that positive attitudes toward ICT facilitate higher digital competencies. More importantly, when attitudes were examined through their affective, cognitive, and behavioral dimensions, behavioral attitude emerged as the strongest predictor of teachers' digital competencies. In addition, contrary to some existing studies, gender did not moderate this relationship significantly. This study contributes valuable insights for designing targeted professional development programs. In particular, the finding that behavioral attitude is the strongest predictor suggests that training initiatives should prioritize hands-on practice and behavioral engagement, rather than focusing solely on knowledge acquisition or gender-based assumptions.

Indexed as

AttitudeSchool TeachersAdultChinaFemaleHumansMaleSex FactorsSurveys and QuestionnairesTeachers’ AttitudesTeachers’ Digital CompetenciesTeachers’ educationTeachers’ GenderTPACK model

Identifiers

PMID42082581
PMCPMC13328540

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.